Tag Archives: revenue forecasting

The holidays are an exciting time at Gnip…and not just because our CEO loves bringing random bottles of excellent Scotch to the office. Around this time of year we get some visibility into the incredible ways our retail and consumer product clients are using social data. In fact, Mashable recently highlighted a study by Mr. Youth (a marketing firm) with an incredible stat that helps prove how valuable social data in holiday shopping truly is:

“66% of respondents who bought something on Black Friday did so as a direct result of social media interactions with friends and family.”

While that stat speaks to the impact social media has upon us as individuals, think more broadly about how powerful it is to analyze that data in aggregate, in real-time. Companies are leveraging data from WordPress blogs, Twitter mentions, Facebook likes and multiple other sources to inform critical realtime decisions for inventory management and operational planning, sales and marketing planning, revenue forecasting, and many others.

Example Scenario for Using Social Data: It’s holiday time, 2011. Your company begins to aggregate ‘mentions’ of a new product from Twitter, Facebook, WordPress blogs in realtime. You take that data and analyze it for # of mentions about the new product, geography of posts (where available), demographic information within user profiles (what keywords are most consistent within Twitter user profiles that mentioned your product?), etc.

Manage supply chain: Redirect inventory to areas with highest potential sales and (depending on how far out you are) use as a data point in the S&OP system for manufacturing forecasts to keep ahead of the holiday demand.

Target marketing spend: Use regional buying patterns and customer habit data to inform what demographic you are, and aren’t, hitting. Do you need to reposition your marketing plan?

Incorporate product feedback: Are there consistent reasons why people are buying your product – or why they aren’t? Information on quality, packaging, price, etc will be incredibly valuable for future products.

Those are just some of the more common use cases we’re seeing. But new opportunities are popping up on a daily basis. We spotted this gem in a recent WSJ article about finding a parking space during crazy shopping times:

Bud Kleppe, a real-estate agent in St. Paul, Minn., watches Mall of America’s Twitter feed for parking updates. (The mall sends them out under the hash tag #moaparking.)

Imagine collecting data from update systems like this and using it measure parking turnover across prime shopping days. Now, overlay the turnover of spots in specific sections against a map of stores and you have some interesting potential for data on economic performance and forecasting. When incorporated with other traditional retail data and compared on a store-to-store basis, you’ve built a unique and realtime analysis tool.

You’re only limited by your imagination in how you can apply social media data to you business. The more software developers, corporations, and people use social media, and the more things they use it for (like parking updates!), the greater the possible use cases for analysis of that data and the more valuable it becomes.